Statistics II for Dummies - Deborah J Rumsey

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Résumé :

Introduction 1

About This Book 1

Foolish Assumptions 3

Icons Used in This Book 3

Beyond the Book 4

Where to Go from Here 4

Part 1: Tackling Data Analysis and Model-Building Basics 7

Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis 9

Data Analysis: Looking before You Crunch 9

Nothing (not even a straight line) lasts forever 10

Data snooping isn't cool 11

No (data) fishing allowed 12

Getting the Big Picture: An Overview of Stats II 13

Population parameter 13

Sample statistic 13

Confidence interval 14

Hypothesis test 14

Analysis of variance (ANOVA) 15

Multiple comparisons 15

Interaction effects 16

Correlation 16

Linear regression 17

Chi-square tests 18

Chapter 2: Finding the Right Analysis for the Job 21

Categorical versus Quantitative Variables 22

Statistics for Categorical Variables 23

Estimating a proportion 23

Comparing proportions 24

Looking for relationships between categorical variables 25

Building models to make predictions 26

Statistics for Quantitative Variables 27

Making estimates 27

Making comparisons 28

Exploring relationships 28

Predicting y using x 30

Avoiding Bias 31

Measuring Precision with Margin of Error 33

Knowing Your Limitations 35

Chapter 3: Having the Normal and Sampling Distributions in Your Back Pocket 37

Recognizing the VIP Distribution - the Normal 38

Characterizing the normal 38

Standardizing to the standard normal (Z-) distribution 38

Using the normal table 40

Finding probabilities for the normal distribution 41

Finally Getting Comfortable with Sampling Distributions 42

The mean and standard error of a sampling distribution 42

Sampling distribution of X 43

Sampling distribution of ?p 44

Heads Up! Building Confidence Intervals and Hypothesis Tests 45

Confidence interval for the population mean 45

Confidence interval for the population proportion 46

Hypothesis test for population mean 46

Hypothesis test for the population proportion 47

Chapter 4: Reviewing Confidence Intervals and Hypothesis Tests 49

Estimating Parameters by Using Confidence Intervals 50

Getting the basics: The general form of a confidence interval 50

Finding the confidence interval for a population mean 51

What changes the margin of error? 52

Interpreting a confidence interval 55

What's the Hype about Hypothesis Tests? 56

What Ho and Ha really represent 56

Gathering your evidence into a test statistic 57

Determining strength of evidence with a p-value 57

False alarms and missed opportunities: Type I and II errors 58

The power of a hypothesis test 60

Part 2: Using Different Types of Regression to Make Predictions 65

Chapter 5: Getting in Line with Simple Linear Regression 67

Exploring Relationships with Scatterplots and Correlations 68

Using scatterplots to explore relationships 69

Collating the information by using the correlation coefficient 70

Building a Simple Linear Regression Model 71

Finding the best-fitting line to model your data 72

The y-intercept of the regression line 73

The slope of the regression line 74

Making point estimates by using the regression line 75

No Conclusion Left Behind: Tests and Confidence Intervals for Regression 75

Scrutinizing the slope 76

In...

Biographie:

Deborah J. Rumsey, PhD, is a Statistics Education Specialist and Associated Professor in the Department of Statistics at The Ohio State University. She is also a Fellow of the American Statistical Association and has received the Presidential Teaching Award from Kansas State University. Dr. Rumsey has published numerous papers and given many professional presentations on the subject of statistics education.